50 Years of Giese Reaction – a Personal View
Bibliographic record
Abstract
Abstract 50 years ago, a synthetic method was discovered, in which alkyl radical precursors, alkenes and hydrogen donors selectively yield 1:1:1‐addition products in cyclic chain reactions. This paved the way for many variants of three‐component syntheses, which became standard procedures for C,C‐bond formation. For successful syntheses the different chain carrying radicals have to follow reactivity and selectivity rules. This requires knowledge of the substituent influence on substrate‐, regio‐ and stereoselectivities of intermolecular radical reactions. These rules were experimentally elucidated, and the synthetic method was coined “Giese reaction”. 20 years after its discovery in the chemical laboratory, biologists observed that microorganisms use the same synthetic strategy, which triggered our studies on biological cells. Although chemical rules in laboratory vessels and biological cells are the same, their different set‐ups lead to very different features. Syntheses in homogeneous solution of a laboratory vessel is driven by kinetic effects. In contrast, most reactions in biological cells occur at protein/water interfaces, where thermodynamic interactions with enzymatic amino acids establish close contact between the educts. In addition, biochemical processes often start with metallo‐cofactors that generate the productive radicals at the interface by long‐distance electron transfer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".